Update train.py

train.py

@@ -58,11 +58,11 @@ LATENT_DIM = 64
 NUM_LAYERS = 3
 LEARNING_RATE = 0.001
 BATCH_SIZE = 64
-NUM_EPOCHS = 50
+NUM_EPOCHS = 100
 MIN_RATING = 3.0
 REG_LAMBDA = 1e-4
 # Evaluation parameters
-TOP_K = [5, 10, 20]  # Top-K for precision and recall calculation
+TOP_K = [5, 10, 20, 30]  # Top-K for precision and recall calculation
 EVALUATION_THRESHOLD = 3.5  # Rating threshold for binary relevance